Bo Zhou
Bo Zhou
https://github.com/PaddlePaddle/PARL/blob/846ebc97fff4e8bcbd9226c82222bef989c139d8/examples/A2C/train.py#L88 The actor runs with the `no wait` mode. Should we wait here until all the weights are set properly?
## How to reproduce the bug: 1. start the master node. 2. add a new worker to the cluster. 3. check the cluster status by calling `xparl status` ## Why...
https://github.com/PaddlePaddle/PARL/blob/develop/parl/core/torch/agent.py#L26
XPARL will not clean the log files after the tasks are finished. The users should be notified if the log files occupy large disk space. I suggest that we can...
How to reproduce the bug? 1. start a task that keeps requesting CPU resources from the cluster. 2. launch the cluster with `xparl start ...`

Note: The algorithm_base in torch should reuse the functions: `get_weights` and `set_weights`, but we rewrite their implementations at the moment.